Sas version 8

Manufactured by SAS Institute

Sourced in United States, Japan

SAS version 8.2 is a software application developed by SAS Institute. It provides a comprehensive platform for data analysis, statistical modeling, and reporting. The core function of SAS version 8.2 is to enable users to manage, analyze, and transform data, as well as create advanced statistical models and reports.

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Lab products found in correlation

Prism 6, by GraphPad (3 mentions) Waters 1525, by Waters Corporation (2 mentions) Sas software, by SAS Institute (2 mentions) Canoco version 5, by Microcomputer Power (1 mentions) Spss version 22, by IBM (1 mentions) Mixed model procedure, by SAS Institute (1 mentions) Ms excel, by SAS Institute (1 mentions) Sigmaplot, by Grafiti LLC (1 mentions) Spss statistics 25, by IBM (1 mentions) Stata 12, by StataCorp (1 mentions) Unscrambler, by CAMO Software (1 mentions) Sigmaplot 13, by Grafiti LLC (1 mentions) Sas stat software, by SAS Institute (1 mentions) Rstudio version 3, by Posit (1 mentions) Jmp version 11, by SAS Institute (1 mentions) Jmp version 10, by SAS Institute (1 mentions) Winnonlin version 5, by Pharsight (1 mentions) Spss version 20, by IBM (1 mentions) Spss version 19, by IBM (1 mentions) Origin software version 8, by OriginLab (1 mentions)

245 protocols using sas version 8

Analyzing Genotype-by-Environment Interactions

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The ANOVA was conducted using GLM procedure in SAS version 8.0 (SAS Institute Inc.), with the following model: y_ger = μ + α_g + β_e + (αβ)_ge + γ_r(e) + ε_ger, where y_ger was the phenotypic trait value of the g^th genotype in the e^th environment for the r^th replicate, μ the grand mean, α_g the genotypic effect of the g^th genotype, β_e the effect of the e^th environment, (αβ)_ge the interaction effect of the g^th genotype and the e^th environment, γ_r(e) the block effect within the e^th environment, and ε_ger the residual. All effects were modeled as random. The CORR procedure in SAS version 8.0 (SAS Institute Inc.) was used to calculate the Pearson’s correlation coefficients between traits of interest. The broad-sense heritability was calculated as: , where , and are estimates of the variances of genotype, genotype × environment interactions, and error, respectively. E is the number of environments, and R is the number of replications per environment.

Lu K., Xiao Z., Jian H., Peng L., Qu C., Fu M., He B., Tie L., Liang Y., Xu X, & Li J. (2016). A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus. Scientific Reports, 6, 36452.

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Thermal Stress Effects on Egg Development

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We analyzed the effects of treatments on the development rate and hatching rate of eggs using a generalized linear model (GLM) with GENMOD procedure in SAS Version 8 followed by planned contrasts based on least-square means to compare the levels of significant differences between treatments. We analyzed the effect of treatment and measuring time on CT_max of first-instar larva using two-way ANOVA and normally distributed errors using the GLM procedure, and the means were separated with Duncan's multiple range tests (P<0.05). To indicate how CT_max of first-instar larvae is linked to changes in degrees of the combination of heat stress and recovery, the relationship between CT_max and cumulative daily average temperature during the egg development was established through linear regression in SAS Version 8.

Bai C.M., Ma G., Cai W.Z, & Ma C.S. (2019). Independent and combined effects of daytime heat stress and night-time recovery determine thermal performance. Biology Open, 8(3), bio038141.

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Serum LH and FSH response to GnRH

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Data were log₁₀ transformed to achieve homogeneity of variance and to increase linearity when appropriate [127 ]. Data were analyzed using Proc GLM with repeated measures (SAS, version 8, SAS Institute Inc., Cary, NC, USA). When log₁₀ transformation failed to normalize data, non-parametric tests were performed (SAS, version 8, SAS Institute Inc., Cary, NC, USA). Paired t-tests were used to determine whether serum LH or FSH increased at 10 min after GnRH injection (0 min vs. 10 min for each animal). p-values of 0.05 or less were taken as significant and are all shown to two decimal places. Data were expressed as the mean ± SEM.

Zhou R., Bruns C.M., Bird I.M., Kemnitz J.W., Dumesic D.A, & Abbott D.H. (2022). Experimentally Induced Hyperinsulinemia Fails to Induce Polycystic Ovary Syndrome-like Traits in Female Rhesus Macaques. International Journal of Molecular Sciences, 23(5), 2635.

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Comparative Analysis of Treatment Effects

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Data were presented as means (±SE) of 3–6 biological replicates. Fisher’s LSD test was used to evaluate significant differences between treatments at P≤0.05. Statistical analyses were performed using SAS version 8.0 (SAS Institute Inc., Cary, NC, USA).

Niu M., Xie J., Chen C., Cao H., Sun J., Kong Q., Shabala S., Shabala L., Huang Y, & Bie Z. (2018). An early ABA-induced stomatal closure, Na+ sequestration in leaf vein and K+ retention in mesophyll confer salt tissue tolerance in Cucurbita species. Journal of Experimental Botany, 69(20), 4945-4960.

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ANOVA Analysis of Experimental Data

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The experimental data was subjected to Analysis of Variance (ANOVA) using SAS version 8.0 (SAS Institute Inc., Cary, NC, United States). ^∗∗ or ^∗ indicated significant difference between means at p < 0.01 or p < 0.05, respectively, by Student’s t-test.

Bai Y., Wu D., Liu F., Li Y., Chen P., Lu M, & Zheng B. (2017). Characterization and Functional Analysis of the Poplar Pectate Lyase-Like Gene PtPL1-18 Reveal Its Role in the Development of Vascular Tissues. Frontiers in Plant Science, 8, 1123.

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Comprehensive Statistical Analysis of Gene Expression and Meat Quality Traits

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The statistically significant difference for gene expression was performed using the unpaired sample t test and one-way analysis of variance (ANOVA) in SPSS 20.0. Here, p < 0.05 was considered to be statistically significant and the data are presented as the mean ± SEM (n = 3). Statistically significant differences for meat color (redness) value a* were assessed using the unpaired sample t test in SPSS 20.0. Here, p < 0.05 was considered to be statistically significant and data are presented as the mean ± SEM (n = 17 and 15). Correlation analysis between the expression of Prox1 and myoglobin, MyHC I, MyHC IIB, MyHC IIX, and phenotype traits was assessed in SPSS 20.0. Statistically significant differences for promoter activity were assessed using ANOVA with Duncan’s multiple range tests in SPSS 20.0. Here, p < 0.05 was considered to be statistically significant and data are presented as the mean ± SEM (n = 5). The association between the polymorphisms of the three selected SNPs (g. −930 bp, g. −1421 bp, g. −1573 bp) and carcass and meat quality traits was assessed using the general linear model (GLM) procedure in SAS version 8.0 (SAS Institute, Cary, NC, USA). The genotype, sex, and batch were used as fixed effects in the model, with carcass weight as a covariate.

Dong C., Zhang X., Liu K., Li B., Chao Z., Jiang A., Li R., Li P., Liu H, & Wu W. (2019). Comprehensive Analysis of Porcine Prox1 Gene and Its Relationship with Meat Quality Traits. Animals : an Open Access Journal from MDPI, 9(10), 744.

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Multivariate Statistical Analysis of Biological Replicates

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Data were presented as the means of 3–6 biological replicates. Duncan’s multiple range tests were used to evaluate significant differences between treatments at P<0.05. Student’s two-sample t-test was also used for comparing the means of two independent samples. Statistical analyses were performed using SAS version 8.0 (SAS Institute Inc., Cary, NC, USA).

Huang Y., Cao H., Yang L., Chen C., Shabala L., Xiong M., Niu M., Liu J., Zheng Z., Zhou L., Peng Z., Bie Z, & Shabala S. (2019). Tissue-specific respiratory burst oxidase homolog-dependent H2O2 signaling to the plasma membrane H+-ATPase confers potassium uptake and salinity tolerance in Cucurbitaceae. Journal of Experimental Botany, 70(20), 5879-5893.

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Statistical Analysis of Categorical and Continuous Data

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All statistical analyses were performed using SAS version 8.0. Categorical variables are shown as frequencies with percentages; they were analyzed using the chi-squared test or Fisher’s exact test. Continuous data are shown as means ± standard deviations or medians (interquartile ranges); they were analyzed using independent-samples t-tests or the Mann–Whitney U test. P-values < 0.05 were considered statistically significant.

Du Q., Pan F., Wang C., Yu F., Shi Y., Liu W., Li Z., He P., Han D, & Zhang H. (2022). Nosocomial dissemination of hypervirulent Klebsiella pneumoniae with high-risk clones among children in Shanghai. Frontiers in Cellular and Infection Microbiology, 12, 984180.

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Statistical Analysis of Experimental Findings

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All experiments were performed in triplicate, and all statistical analyses were performed using SAS version 8.0 software (SAS Institute, Inc.). Differences in mean values were considered significant when P < 0.05. The histogram was created using Microsoft Excel 2010 (Microsoft, Redmond, WA, USA).

Wang X., Wang C., Sui J., Liu Z., Li Q., Ji C., Song X., Hu Y., Wang C., Sa R., Zhang J., Du J, & Liu X. (2018). Isolation and characterization of phosphofungi, and screening of their plant growth-promoting activities. AMB Express, 8, 63.

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Statistical Analysis of Isolate Variance

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Data for the growth rate and RAUDPC of each isolate were subjected to statistical analysis of significant variance among replicates using SAS Version 8.0 (SAS Institute, Cary, NC, 1999). Treatment means for each of these parameters for the tested isolates were compared using the least-significant-difference test at P < 0.05.

Wang J., Ni Y., Liu X., Zhao H., Xiao Y., Xiao X., Li S, & Liu H. (2020). Divergent RNA viruses in Macrophomina phaseolina exhibit potential as virocontrol agents. Virus Evolution, 7(1), veaa095.

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